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Exposure to Automated Drug Alerts Over Time

Effects On Clinicians’ Knowledge And Perceptions

Datos Bibliográficos

ID9099367
AutoresPeter A Glassman, Peter Glassman (VA Greater Los Angeles Healthcare System, autor de correspondencia), Pamela Belperio, Pamela S Belperio (0000-0002-6435-7450, VA Greater Los Angeles Healthcare System, autor de correspondencia), Barbara Simon (0009-0001-7260-5557, VA Greater Los Angeles Healthcare System, autor de correspondencia), Andrew B Lanto (VA Greater Los Angeles Healthcare System, autor de correspondencia), Andrew Lanto, Martin Lee (0000-0002-6004-3622, Center for the Study of Healthcare Provider Behavior, autor de correspondencia)
Año2006
Volumen44
Número3
Páginas250-256
Fecha de publicación2006-03-01
Peer ReviewedSí
Open AccessNo
TipoARTICLE
RevistaMedical Care (JOURNAL)
Identificadores de la revistaISSN: 0025-7079 • E-ISSN: 1537-1948
EditorialOvid Technologies (Wolters Kluwer Health) (PUBLISHER)
DOI10.1097/01.mlr.0000199849.08389.91
PMID16501396
OpenAlexW2052752050
IdiomaEN
Citas recibidas1
Referencias citadas13

OBJECTIVE: We tested whether interval exposure to an automated drug alert system that included approximately 2000 drug-drug interaction alerts increased recognition of selected interacting drug pairs. We also examined other perceptions about computerized order entry. RESEARCH DESIGN: We administered cross-sectional surveys in 2000 and 2002 that included more than 260 eligible clinicians in each time period. SUBJECTS: We studied clinicians practicing in ambulatory settings within a Southern California Veterans Affairs Healthcare System and who responded to both surveys (97 respondents). MEASURES: We sought to measure (1) recognition of selected drug-drug and drug-condition interactions and (2) other benefits and barriers to using automated drug alerts. RESULTS: Clinicians correctly categorized similar percentages of the 7 interacting drug-drug pairs at baseline and follow-up (53% vs. 54%, P = 0.51) but improved their overall recognition of the 3 contraindicated drug-drug pairs (51% vs. 60%, P = 0.01). No significant changes from baseline to follow-up were found for the 8 interacting drug-condition pairs (60% vs. 62%, P = 0.43) or the 4 contraindicated drug-condition pairs (52% vs. 56%, P = 0.24). More providers preferred using order entry at follow-up than baseline (63% vs. 45%, P < 0.001). Signal-to-noise ratio remained the biggest reported problem at follow-up and baseline (54 vs. 57%, P = 0.75). In 2002, clinicians reported seeing a median of 5 drug alerts per week (representing approximately 12.5% of prescriptions entered), with a median 5% reportedly leading to an action. CONCLUSIONS: Interval exposure to automated drug alerts had little to no effect on recognition of selected drug-drug interactions. The primary perceived barrier to effective utilization of drug alerts remained the same over time

Ambulatory · Confidence interval · Drug · Drug-drug interaction · Medical prescription · Electronic Health Records Systems · Emergency Medicine · Internal Medicine · Medicine · Pharmaceutical Practices and Patient Outcomes · Pharmacology · Pharmacovigilance and Adverse Drug Reactions

  • Pharmacist Workload and Pharmacy Characteristics Associated With the Dispensing of Potentially Clinically Important Drug-Drug Interactions

    Daniel C Malone, Jacob Abarca et al.•Medical Care•2007

  • Improving Recognition of Drug Interactions

    Peter A Glassman, Peter Glassman et al.•Medical Care•2002

Obras citantes distintas1
Citas por año0,05
Intervalo de citas2007 - 2007 (1)
Velocidad de citaciónhistorical
Altamente citadoNo
Tipos de citaNeutras: 1

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